Home

Row

Tweets Today

387

Tweeters Today

144

#rstats Likes

422922

#rstats Tweets

43470

Row

Tweet volume

Tweets by Hour of Day

Row

💗 Most Liked Tweet Today

✨ Most Retweeted Tweet Today

Data

---
title: "#rstats Twitter Explorer"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: scroll
    source_code: embed
    theme:
      version: 4
      bootswatch: yeti
    css: styles/main.css
---

```{r setup, include=FALSE}
library(flexdashboard)
library(rtweet)
library(dplyr)
library(httr)
library(lubridate)
library(echarts4r)
devtools::load_all()

rstats_tweets <- read_twitter_csv("data/rstats_tweets.csv")

count_timeseries <- rstats_tweets %>%
  ts_data(by = "hours")

tweets_today <- rstats_tweets %>%
  filter(created_at == today())

by_hour <- rstats_tweets %>%
  group_by(hour = hour(created_at)) %>%
  summarise(count = n()) %>%
  ungroup()

number_of_unique_tweets <- get_unique_value(rstats_tweets, text)

number_of_unique_tweets_today <-
  get_unique_value(tweets_today, text)

number_of_tweeters_today <- get_unique_value(tweets_today, user_id)

number_of_likes <- rstats_tweets %>%
  pull(favorite_count) %>%
  sum()
```


Home
====

Row
-----------------------------------------------------------------------

### Tweets Today

```{r}
valueBox(number_of_unique_tweets_today, icon = "fa-comment-alt", color = "plum")
```

### Tweeters Today

```{r}
valueBox(number_of_tweeters_today, icon = "fa-user", color = "peachpuff")
```

### #rstats Likes

```{r}
valueBox(number_of_likes, icon = "fa-heart", color = "palevioletred")
```

### #rstats Tweets

```{r}
valueBox(number_of_unique_tweets, icon = "fa-comments", color = "mediumorchid")
```

Row {.tabset .tabset-fade data-width=400}
-----------------------------------------------------------------------

### Tweet volume

```{r}
this_month <- floor_date(today(), "month")

count_timeseries %>%
  e_charts(time) %>%
  e_line(n, name = "# of tweets", smooth = TRUE, legend = FALSE) %>%
  e_x_axis(
    type = "time",
    formatter = htmlwidgets::JS(
      "function(value){
        let date = new Date(value);
        
        label = `${date.getDate()}-${(parseInt(date.getMonth()) + 1)}-${date.getFullYear()}`;
        return label;
      }"
    )
  ) %>%
  e_axis_labels(y = "Tweets") %>%
  e_theme("westeros") %>%
  e_tooltip(trigger = "axis", formatter = htmlwidgets::JS("
    function(params) {
      let date = new Date(params[0].value[0])
      let options = { year: 'numeric', month: 'short', day: 'numeric', hour: 'numeric'}
      let title = `${date.toLocaleDateString('en-US', options=options)}`
      let num = `${params[0].value[1]} tweets`
      return(`${title}
${num}`); }")) %>% e_datazoom(type = "slider") %>% e_zoom( dataZoomIndex = 0, start = 70, end = 100 ) %>% e_zoom( dataZoomIndex = 0, startValue = today() - 7, endValue = today(), btn = "weekBtn" ) %>% e_zoom( dataZoomIndex = 0, startValue = this_month, endValue = today(), btn = "monthBtn" ) %>% e_button( id = "weekBtn", position = "top", class = "btn btn-primary btn-sm", "This Week" ) %>% e_button( id = "monthBtn", position = "top", class = "btn btn-primary btn-sm", "This Month" ) ``` ### Tweets by Hour of Day ```{r} by_hour %>% e_charts(hour) %>% e_step(count, name = "Tweets", step = "middle", legend = FALSE) %>% e_x_axis( min = 0, max = 23, ) %>% e_axis_labels(x = "Time of Day (UTC)", y = "Tweets") %>% e_theme("westeros") %>% e_tooltip(trigger = "axis", formatter = htmlwidgets::JS(" function(params) { let title = `${params[0].value[0]}h` let num = `${params[0].value[1]} tweets` return(`${title}
${num}`); }")) ``` Row ----------------------------------------------------------------------- ### 💗 Most Liked Tweet Today {.tweet-box} ```{r} most_liked_url <- tweets_today %>% slice_max(favorite_count) get_tweet_embed(most_liked_url$screen_name, most_liked_url$status_id) ``` ### ✨ Most Retweeted Tweet Today {.tweet-box} ```{r} most_retweeted <- tweets_today %>% slice_max(retweet_count) get_tweet_embed(most_retweeted$screen_name, most_retweeted$status_id) ``` ### 🎉 Most Recent {.tweet-box} ```{r} most_recent <- tweets_today %>% slice_max(created_at, with_ties=FALSE) get_tweet_embed(most_recent$screen_name, most_recent$status_id) ``` Data ====